04262018_SH1_full
Start up functions
Read and organize data
read_srm_export <- function(filename, columns = c("peak_name", "RT.min", "basepeak", "area.cpm", "height.cts", "quantitation")) {
filename %>%
# read excel files
read_excel(sheet = "Integration", skip = 42,
col_names = columns, col_types = rep("text", length(columns))) %>%
as_data_frame() %>%
# remove empty rows
filter(!is.na(peak_name), peak_name != "n.a.") %>%
# convert the relevant numeric columns into numbers
mutate_at(vars(RT.min, area.cpm, height.cts), as.numeric) %>%
# remove useless columns
select(-basepeak, -quantitation) %>%
# add filename info
mutate(file_id = gsub("\\.xls", "", basename(filename))) %>%
select(file_id, everything())
}
# get data
all_data <-
# find all excel files ##change name and use new folder for new project
list.files("data_SH1", recursive = TRUE, full.names = TRUE, pattern = "\\.xls$") %>%
# send them to the read method
lapply(read_srm_export) %>%
# combine the data set
bind_rows() %>%
# pull out sample information
#mutate(sample_id = str_match(all_data$file_id, "TSQ\\d+_GB_(.*)$") %>% { .[,2] }) %>%
# get n replicates
group_by(file_id)
#mutate(n_replicates = length(unique(file_id)))Calculation peak amounts and rock concentrations, ID standards
depth_and_rock_info <- read_excel(file.path("metadata", "aliphaticSRM_SH1.xlsx")) %>%
rename(tle = `TLE.mg`, maltene = `maltenes.mg`, ref_amount_added.ug = `D4.ug` )%>%
filter(!is.na(file_id)) %>%
filter (process == "yes")
depth_and_rock_info## # A tibble: 68 x 8
## file_id OG depth rock.g tle maltene ref_amount_adde… process
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 TSQ3481_G… 2.00 125 10.0 24.9 13.7 100 yes
## 2 TSQ3482_G… 3.00 124 10.1 224 7.30 100 yes
## 3 TSQ3483_G… 4.00 123 10.3 - 14.4 5.00 100 yes
## 4 TSQ3484_G… 5.00 122 9.28 3.20 5.40 100 yes
## 5 TSQ3485_G… 6.00 121 10.6 33.4 NA 100 yes
## 6 TSQ3486_G… 7.00 119 9.62 -214 4.80 100 yes
## 7 TSQ3489_G… 8.00 118 9.70 3.40 5.00 100 yes
## 8 TSQ3490_G… 9.00 117 10.7 5.00 6.30 100 yes
## 9 TSQ3491_G… 10.0 115 11.1 5.00 6.00 100 yes
## 10 TSQ3492_G… 11.0 114 10.2 0.400 6.90 100 yes
## # ... with 58 more rowsdata_by_depth <-
all_data %>%
left_join(depth_and_rock_info, by = "file_id") %>%
group_by(file_id) %>%
mutate(
n_peaks = n(),
n_standards = sum(peak_name == "D4 C29 ISTD"),
ref_area.cpm = area.cpm[peak_name == "D4 C29 ISTD"],
amount.ug = area.cpm/ref_area.cpm * ref_amount_added.ug,
#Normalize by what you want
conc_rock.ug_g = amount.ug / rock.g,
conc_tle.ug.g = amount.ug / tle,
conc_maltene.ug.g = amount.ug / maltene
)%>% ungroup() %>%
arrange(file_id, peak_name)
data_by_depth## # A tibble: 11,665 x 19
## file_id peak_name RT.min area.cpm height.cts OG depth rock.g tle
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TSQ3466… 20R 4a,24… 34.7 42909 396389 22.0 102 11.0 4.50
## 2 TSQ3466… 20R, 4a M… 33.4 33439 425331 22.0 102 11.0 4.50
## 3 TSQ3466… 20R, 4a M… 32.8 49529 763046 22.0 102 11.0 4.50
## 4 TSQ3466… 20R, 4a,2… 35.3 26212 404760 22.0 102 11.0 4.50
## 5 TSQ3466… 20S, 4a M… 32.1 49207 882869 22.0 102 11.0 4.50
## 6 TSQ3466… 20S, 4a,2… 35.8 31831 268610 22.0 102 11.0 4.50
## 7 TSQ3466… 20S, 4a,2… 34.0 51613 456842 22.0 102 11.0 4.50
## 8 TSQ3466… 25-nor C2… 37.6 11915 155542 22.0 102 11.0 4.50
## 9 TSQ3466… 28, 30 C2… 37.0 27403 343070 22.0 102 11.0 4.50
## 10 TSQ3466… 29, 30 C2… 35.8 5780 63220 22.0 102 11.0 4.50
## # ... with 11,655 more rows, and 10 more variables: maltene <dbl>,
## # ref_amount_added.ug <dbl>, process <chr>, n_peaks <int>,
## # n_standards <int>, ref_area.cpm <dbl>, amount.ug <dbl>,
## # conc_rock.ug_g <dbl>, conc_tle.ug.g <dbl>, conc_maltene.ug.g <dbl>Calculate Recovery
Linear regressions of the calibration curves
standard <- read_excel(file.path("metadata", "D4_calibration.xlsx")) ###read excel
###calibration curve
standard %>%
ggplot() +
aes(x = Known.ng, y = Measured_area.counts, color = calibration) +
geom_smooth(method = "lm", alpha = 0.5) +
geom_point() +
theme_bw() +
theme(legend.position = "none") 
calibrations <-
standard %>%
filter(!is.na(calibration)) %>%
nest(-calibration) %>%
mutate(
fit = map(data, ~summary(lm(`Measured_area.counts`~ `Known.ng`, data = .x))),
coefficients = map(fit, "coefficients"),
intercept = map_dbl(coefficients, `[`, 1, 1),
intercept_se = map_dbl(coefficients, `[`, 1, 2),
slope = map_dbl(coefficients, `[`, 2, 1),
slope_se = map_dbl(coefficients, `[`, 2, 2),
r2 = map_dbl(fit, "r.squared")
)
calibrations %>% select(-data, -fit, -coefficients) %>% knitr::kable(d = 3)| calibration | intercept | intercept_se | slope | slope_se | r2 |
|---|---|---|---|---|---|
| jan2018 | 705.862 | 1371.146 | 72929.67 | 3337.256 | 0.996 |
Determine yield
These numbers are not useful for anything else.
calib_data <-
data_by_depth %>%
# temp
mutate(calibration = "jan2018") %>%
left_join(calibrations, by = "calibration") %>%
mutate(
total_volume.uL = 100,
total_inject.uL = 1.5,
ref_amount_inject_expected.ng = (ref_amount_added.ug * 1000)/total_volume.uL * total_inject.uL ,
ref_amount_inject_measured.ng = (ref_area.cpm - intercept)/slope,
ref_amount_measured.ug = ((total_volume.uL* ref_amount_inject_measured.ng)/total_inject.uL) * 1/1000,
yield = (ref_amount_inject_measured.ng/ref_amount_inject_expected.ng) * 100
)
calib_data## # A tibble: 11,665 x 34
## file_id peak_name RT.min area.cpm height.cts OG depth rock.g tle
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TSQ3466… 20R 4a,24… 34.7 42909 396389 22.0 102 11.0 4.50
## 2 TSQ3466… 20R, 4a M… 33.4 33439 425331 22.0 102 11.0 4.50
## 3 TSQ3466… 20R, 4a M… 32.8 49529 763046 22.0 102 11.0 4.50
## 4 TSQ3466… 20R, 4a,2… 35.3 26212 404760 22.0 102 11.0 4.50
## 5 TSQ3466… 20S, 4a M… 32.1 49207 882869 22.0 102 11.0 4.50
## 6 TSQ3466… 20S, 4a,2… 35.8 31831 268610 22.0 102 11.0 4.50
## 7 TSQ3466… 20S, 4a,2… 34.0 51613 456842 22.0 102 11.0 4.50
## 8 TSQ3466… 25-nor C2… 37.6 11915 155542 22.0 102 11.0 4.50
## 9 TSQ3466… 28, 30 C2… 37.0 27403 343070 22.0 102 11.0 4.50
## 10 TSQ3466… 29, 30 C2… 35.8 5780 63220 22.0 102 11.0 4.50
## # ... with 11,655 more rows, and 25 more variables: maltene <dbl>,
## # ref_amount_added.ug <dbl>, process <chr>, n_peaks <int>,
## # n_standards <int>, ref_area.cpm <dbl>, amount.ug <dbl>,
## # conc_rock.ug_g <dbl>, conc_tle.ug.g <dbl>, conc_maltene.ug.g <dbl>,
## # calibration <chr>, data <list>, fit <list>, coefficients <list>,
## # intercept <dbl>, intercept_se <dbl>, slope <dbl>, slope_se <dbl>,
## # r2 <dbl>, total_volume.uL <dbl>, total_inject.uL <dbl>,
## # ref_amount_inject_expected.ng <dbl>,
## # ref_amount_inject_measured.ng <dbl>, ref_amount_measured.ug <dbl>,
## # yield <dbl>calib_data %>%
select(file_id, peak_name, yield) %>%
arrange(file_id) %>%
unique() %>%
ggplot() + aes(file_id, y = yield) +
geom_point(size = 3) +
theme_bw() + theme(axis.text.x = element_text(angle = 90, hjust = 0, vjust = 0.5))## Warning: Removed 2186 rows containing missing values (geom_point).
Ratios
Functions for ratios and sums
sum_peaks <- function(df, filter_condition, new_peak_name) {
filter_condition <- sprintf("(%s)", str_c(filter_condition, collapse = "|"))
filter(df, str_detect(peak_name, filter_condition)) %>%
summarize(
file_id = file_id[1],
depth = depth[1],
conc_rock.ug_g = sum(conc_rock.ug_g)
) %>%
mutate(peak_name = new_peak_name)
}
ratio_peaks <- function(df, filter_top, filter_bottom, new_peak_name) {
filter_top <- sprintf("(%s)", str_c(filter_top, collapse = "|"))
filter_bottom <- sprintf("(%s)", str_c(filter_bottom, collapse = "|"))
filter(df, str_detect(peak_name, filter_top) | str_detect(peak_name, filter_bottom)) %>%
summarize(
file_id = file_id[1],
depth = depth[1],
ratio = sum(conc_rock.ug_g[str_detect(peak_name, filter_top)]) / sum(conc_rock.ug_g[str_detect(peak_name, filter_bottom)])
) %>%
mutate(peak_name = new_peak_name)
}Combine compounds, calculate ratios
#set values to use for later calculations
final_data1 <- calib_data %>%
group_by(file_id) %>%
do({
bind_rows(.,
#C27_Dia/Reg
sum_peaks(., c("C27 aB 20R ST", "C27 aB 20S ST"), "C27Dia"),
sum_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST"), "C27Reg"),
#Total Tricyclics
sum_peaks(., c("C19 Tri HO", "C20 Tri HO", "C21 Tri HO", "C22 Tri HO", "C23 Tri HO", "C24 Tet HO", "C24 Tri HO", "C25 Tri R+S HO", "C26 Tri R HO", "C26 Tri S HO"), "all_tricyclics"),
#4Me_TriMe
sum_peaks(., c("4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane"), "4Me_TriMe"),
#allRegSt
sum_peaks(., c("C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST","C27 aBB 20S ST", "C27 aBB 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST","C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aBB 20 R+S ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "allRegst"),
#allRegHO
sum_peaks(., c("Ts C27 HO", "Tm C27 HO", "C27 17B H Ho", "29, 30 C28H bisnor HO", "28, 30 C28 bisnor HO", "C29 Ts HO", "C29 Ba HO", "C29 BB Ho", "C30 aB HO", "C30 BB HO", "C30H Ba HO", "C31 HR Ba HO", "C31 aB HR HO", "C31 aB HS HO", "C31 BB HO", "C32 aB HS HO", "C32 aB HR HO", "C33 aB HS HO", "C33 aB HR HO", "C34 aB HR HO", "C34 aB HS HO", "C35 aB HR HO", "C35 aB HS HO"), "allRegHO") ,
#allDiacholestane
sum_peaks(., c("20S, 4a Me 13B,17a,H diacholestane", "20R, 4a Me 13B,17a,H diacholestane" , "20R, 4a Me 13a,17B,H diacholestane", "20S, 4a,24 dimethyl 13B,17a,H diacholestane", "20R 4a,24 dimethyl 13B,17a,H diacholestane", "20R, 4a,24 dimethyl 13a,17B,H diacholestane" , "20S, 4a,24 dimethyl 13a,17B,H diacholestane", "4a,24 dimethyl 5a cholestane" , "4B,24 dimethyl 5a cholestane"), "allDiacholestane"),
#all Steranes
sum_peaks(., c("C26 Ba 20S ST", "C26 Ba 20R ST", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST", "C28 Ba 20S ST", "C28 Ba 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST" , "C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST" , "C30 Ba 20S ST", "C30 Ba 20R ST", "C30 aBB 20(R+S) ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C30 4a Me 20S ST", "C30 4a Me 20R ST + DINO st", "C30 3B Me BB 20S ST", "C30 3B Me 20S ST + C30 3B Me BB 20R ST" , "C30 3BMe 20R ST", "C30 2aMe 20S ST", "C30 2a Me 20R + 4a Me BB 20S ST" , "4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane", "20S, 4a Me 13B,17a,H diacholestane", "20R, 4a Me 13B,17a,H diacholestane" , "20R, 4a Me 13a,17B,H diacholestane", "20S, 4a,24 dimethyl 13B,17a,H diacholestane", "20R 4a,24 dimethyl 13B,17a,H diacholestane", "20R, 4a,24 dimethyl 13a,17B,H diacholestane" , "20S, 4a,24 dimethyl 13a,17B,H diacholestane", "4a,24 dimethyl 5a cholestane" , "4B,24 dimethyl 5a cholestane"), "allSteranes"),
#everything
sum_peaks(., c(""), "everything")
) }) %>% ungroup()final_data <- final_data1 %>%
group_by(file_id) %>%
do({
bind_rows(.,
#Source
#C19/tricyclics
ratio_peaks(., "C19 Tri HO", "all_tricyclics", "C19/tricyclics"),
#C20/tricyclics
ratio_peaks(., "C20 Tri HO", "all_tricyclics", "C20/tricyclics"),
#C21/tricyclics
ratio_peaks(., "C21 Tri HO", "all_tricyclics", "C21/tricyclics"),
#C22/tricyclics
ratio_peaks(., "C22 Tri HO", "all_tricyclics", "C22/tricyclics"),
#C23/tricyclics
ratio_peaks(., "C23 Tri HO", "all_tricyclics", "C23/tricyclics"),
#C24/tricyclics
ratio_peaks(., c("C24 Tet HO", "C24 Tri HO"), "all_tricyclics", "C24/tricyclics"),
#C25/tricyclics
ratio_peaks(., "C25 Tri R+S HO", "all_tricyclics", "C25/tricyclics"),
#C26/tricyclics
ratio_peaks(., c("C26 Tri R HO", "C26 Tri S HO"), "all_tricyclics", "C26/tricyclics"),
#tricyclics/all
ratio_peaks(., "all_tricyclics", c(""), "tricyclics/all"),
#C19/C19+23
ratio_peaks(., "C19 Tri HO", c("C19 Tri HO", "C23 Tri HO"), "C19/C19+23"),
#C20/C20+23
ratio_peaks(., "C20 Tri HO", c("C20 Tri HO", "C23 Tri HO"), "C20/C20+23"),
#Ho/St
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "Ho/St"),
#Ho/St%
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO" ), "Ho/St%"),
#C31_2MHI
ratio_peaks(., "C31 2a Me Ho", c("C30 aB HO", "C31 2a Me Ho" ), "C31_2MHI"),
#C31_35_2MHI
ratio_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), c("C30 aB HO", "C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), "C31_35_2MHI"),
#C31_2-MHI/C27-C30Steranes
ratio_peaks(., "C31 2a Me Ho", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST" ,"C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C31 2a Me Ho" ), "C31_2-MHI/C27-C30Steranes"),
#C31 3-MHI
ratio_peaks(., "C31 3B Me HO", c("C31 3B Me HO", "C30 aB HO"), "C31 3-MHI"),
#C31_35_3MHI(%)
ratio_peaks(., c("C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S Ho", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO"), c("C30 aB HO","C31 3B Me HO", "C32 3B Me S HO", "C32 3B Me R HO", "C32 3B Me Ba 22S+R ST", "C33 3BMe S HO", "C33 3BMe R HO", "C34 3B Me S HO", "C34 3B Me R HO", "C35 3B Me R HO", "C35 3B Me S HO", "C36 3B Me S HO", "C36 3B Me R HO" ) ,"C31_35_3MHI(%)"),
#C29ab/C29ab+C30ab
ratio_peaks(., "C29 aB HO", c( "C29 aB HO" , "C30 aB HO"), "C29ab/C29ab+C30ab"),
#C29ab/allHoab
ratio_peaks(., "C29 aB HO" , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C29ab/allHoab"),
#C30ab/allHoab
ratio_peaks(., "C30 aB HO" , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C30ab/allHoab"),
#C31ab/allHoab
ratio_peaks(., c("C31 aB HS HO", "C31 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C31ab/allHoab"),
#C32ab/allHoab
ratio_peaks(., c("C32 aB HR HO", "C32 aB HS HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C32ab/allHoab"),
#C33ab/allHoab
ratio_peaks(., c( "C33 aB HS HO" , "C33 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C33ab/allHoab"),
#C34ab/allHoab
ratio_peaks(., c( "C34 aB HS HO", "C34 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C34ab/allHoab"),
#C35ab/allHoab
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO", "C30 aB HO", "C29 aB HO"), "C35ab/allHoab"),
#OleananeIndex
ratio_peaks(., "Oleanane HO", c("Oleanane HO", "C30 aB HO"), "OleananeIndex"),
#HHI
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO") , c("C35 aB HS HO", "C35 aB HR HO", "C34 aB HS HO", "C34 aB HR HO", "C33 aB HS HO" , "C33 aB HR HO", "C32 aB HR HO", "C32 aB HS HO", "C31 aB HS HO", "C31 aB HR HO"), "HHI"),
#C35/C35+C34
ratio_peaks(., c("C35 aB HS HO", "C35 aB HR HO"), c("C34 aB HS HO", "C34 aB HR HO","C35 aB HS HO", "C35 aB HR HO"), "C35/C35+C34"),
#GI
ratio_peaks(., "gamma", c("gamma", "C30 aB HO"), "GI"),
#28,30BNH/28,30BNH+C30
ratio_peaks(., "28, 30 C28 bisnor HO", c("28, 30 C28 bisnor HO", "C30 aB HO"), "28,30BNH/28,30BNH+C30") ,
#Source
#C26St/allSt ##INCLUDES ME's
ratio_peaks(., c("C26 Ba 20S ST", "C26 Ba 20R ST", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST"), "allSteranes", "C26St/allSt"),
#C27St/allSt
ratio_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C27 Ba 20R ST", "C27 Ba 20S ST"), "allSteranes", "C27St/allSt"),
#C28St/allSt
ratio_peaks(., c("C28 Ba 20S ST", "C28 Ba 20R ST", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST"), "allSteranes", "C28St/allSt"),
#C29St/allSt
ratio_peaks(., c("C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST"), "allSteranes", "C29St/allSt"),
#C30St/allSt (does not include Me's in numerator)
ratio_peaks(., c("C30 Ba 20S ST", "C30 Ba 20R ST", "C30 aBB 20(R+S) ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "allSteranes", "C30St/allSt"),
#C30Me/allSt (C30 Me's in numerator)(not in MRM spreadsheet)
ratio_peaks(., c("C30 4a Me 20S ST", "C30 4a Me 20R ST + DINO st", "C30 3B Me BB 20S ST", "C30 3B Me 20S ST + C30 3B Me BB 20R ST", "C30 3BMe 20R ST", "C30 2aMe 20S ST", "C30 2a Me 20R + 4a Me BB 20S ST"), "allSteranes", "C30Me/allSt"),
#DinoSt/allSt
ratio_peaks(., c("4B Me 5a cholestane", "4B Me 24 ethyl 5a cholestane", "4B,23S,24S trimethyl 5a cholestane", "4B,23S,24R trimethyl 5a cholestane", "4B,23R,24S trimethyl 5a cholestane", "4B,23R,24R trimethyl 5a cholestane", "4a Me 5a cholestane", "4a Me 24 ethyl 5a cholestane", "4a,23S,24S trimethyl 5a cholestane", "4a,23S,24R trimethyl 5a cholestane", "4a,23R,24S trimethyl 5a cholestane", "4a,23R,24R trimethyl 5a cholestane"), "allSteranes", "DinoSt/allSt"),
#C26/(C26-30)aaaSR
ratio_peaks(., c("C26 aaa 20R ST", "C26 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C26/(C26-30)aaaSR"),
#C27/(C26-30)aaaSR
ratio_peaks(., c("C27 aaa 20R ST", "C27 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C27/(C26-30)aaaSR"),
#C28/(C26-30)aaaSR
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C28/(C26-30)aaaSR"),
#C29/(C26-30)aaaSR
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C29/(C26-30)aaaSR"),
#C30/(C26-30)aaaSR
ratio_peaks(., c("C30 aaa 20R ST", "C30 aaa 20S ST"), c("aaa 20R ST", "aaa 20S ST") , "C30/(C26-30)aaaSR"),
#C27/C27+C28aaa&abb
ratio_peaks(., c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C27/C27+C28aaa&abb"),
#C27/C27+C29aaa&abb
ratio_peaks(., c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST") , "C27/C27+C29aaa&abb"),
#C28/C28+C27aaa&abb
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C28/C28+C27aaa&abb"),
#C28/C28+C29aaa&abb
ratio_peaks(., c("C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST"), c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C28/C28+C29aaa&abb"),
#C29/C29+C27aaa&abb
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST"), c("C27 aaa 20R ST" , "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST", "C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST") , "C29/C29+C27aaa&abb"),
#C29/C29+C28aaa&abb
ratio_peaks(., c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST"), c("C29 aaa 20R ST", "C29 aaa 20S ST", "C29 aBB 20R ST", "C29 aBB 20S ST", "C28 aaa 20R ST", "C28 aaa 20S ST", "C28 aBB 20R ST", "C28 aBB 20S ST") , "C29/C29+C28aaa&abb"),
#4Me_TriMe/Me_C26St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C26 aBB 20S ST", "C26 aBB 20R ST", "C26 aaa 20S ST", "C26 aaa 20R ST") , "4Me_TriMe/Me_C26St"),
#4Me_TriMe/Me_C27St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C27 aBB 20S ST", "C27 aBB 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST") , "4Me_TriMe/Me_C27St"),
#4Me_TriMe/Me_C28St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST") , "4Me_TriMe/Me_C28St"),
#4Me_TriMe/Me_C29St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST") , "4Me_TriMe/Me_C29St"),
#4Me_TriMe/Me_C30St
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "C30 aBB 20 R+S ST", "C30 aaa 20S ST", "C30 aaa 20R ST") , "4Me_TriMe/Me_C30St"),
#4Me_TriMe/Me_allSt
ratio_peaks(., c("4Me_TriMe"), c("4Me_TriMe", "allRegst") , "4Me_TriMe/Me_allSt"),
#Dino/all
ratio_peaks(., "allDiacholestane", c("allSteranes", "allRegHO"), "Dino/all"),
#C26-30St/C26-C30St+regHo
ratio_peaks(., c("allRegst"), c("allRegst", "Ts C27 HO", "Tm C27 HO", "C27 17B HO", "29, 30 C28 bisnor HO", "28, 30 C28 bisnor HO", "C29 Ts HO", "C29 Ba HO", "C29 BB Ho", "C30 aB HO", "C30 BB HO", "C30H Ba HO", "C31 HR Ba HO", "C31 aB HR HO", "C31 aB HS HO", "C31 BB HO", "C32 aB HS HO", "C32 aB HR HO", "C33 aB HS HO", "C33 aB HR HO", "C34 aB HR HO", "C34 aB HS HO", "C35 aB HR HO", "C35 aB HS HO"), "C26-30St/C26-C30St_regHo"),
#C27-C30aaaSt/C27-C30aaaSt+regHo
ratio_peaks(., c( "C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO"), "C27-C30aaaSt/C27-C30aaaSt+regHo"),
#Ho/St
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST"), "Ho/St"),
#Ho/St%
ratio_peaks(., "allRegHO", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "allRegHO" ), "Ho/St%"),
#C31_2MHI
ratio_peaks(., "C31 2a Me Ho", c("C30 aB HO", "C31 2a Me Ho" ), "C31_2MHI"),
#C31_35_2MHI
ratio_peaks(., c("C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), c("C30 aB HO", "C31 2a Me Ho", "C32 2aMe R HO", "C32 2aMe S HO", "C33 2aMe S HO", "C33 2aMe R HO", "C34 2a Me S HO", "C34 2a Me R HO", "C36 2a Me R HO", "C36 2a Me S HO"), "C31_35_2MHI"),
#C31_2-MHI/C27-C30Steranes
ratio_peaks(., "C31 2a Me Ho", c("C26 aaa 20S ST", "C26 aaa 20R ST", "C27 aaa 20S ST", "C27 aaa 20R ST" ,"C28 aaa 20S ST", "C28 aaa 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST", "C30 aaa 20S ST", "C30 aaa 20R ST", "C31 2a Me Ho" ), "C31_2-MHI/C27-C30Steranes"),
#Thermal Maturity
#C27_Dia/Reg
ratio_peaks(., "C27Dia", "C27Reg", "C27Dia/Reg"),
#C27Dia_S/R
ratio_peaks(., "C27 aB 20S ST", "C27 aB 20R ST", "C27Dia_S/R"),
#C27Dia_S/S+R
ratio_peaks(., "C27 aB 20S ST", c("C27 aB 20S ST", "C27 aB 20R ST"), "C27Dia_S/S+R") ,
#C27Reg_abb/all
ratio_peaks(., c("C27 aBB 20R ST", "C27 aBB 20S ST"), c("C27 aaa 20R ST", "C27 aaa 20S ST", "C27 aBB 20R ST", "C27 aBB 20S ST"), "C27Reg_abb/aaa"),
#C27RegaaaS/S+R
ratio_peaks(., "C27 aaa 20S ST", c("C27 aaa 20R ST", "C27 aaa 20S ST"), "C27Regaaa_S/S+R"),
#C27RegabbS/S+R
ratio_peaks(., "C27 aBB 20S ST", c("C27 aBB 20S ST", "C27 aBB 20R ST"), "C27Regabb_S/S+R"),
#C28Dia/all
ratio_peaks(., c("C28 Ba 20S ST", "C28 Ba 20R ST"), c("C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST", "C28 Ba 20S ST", "C28 Ba 20R ST"), "C28Dia/all"),
#C28DiaS/S+R
ratio_peaks(., "C28 Ba 20S ST", c("C28 Ba 20S ST", "C28 Ba 20R ST"), "C28DiaS/S+R"),
#C28abb/all
ratio_peaks(., c("C28 aBB 20S ST", "C28 aBB 20R ST"), c("C28 aBB 20S ST", "C28 aBB 20R ST", "C28 aaa 20S ST", "C28 aaa 20R ST"), "C28abb/all"),
#C28aaaS/S+R
ratio_peaks(., "C28 aaa 20S ST", c("C28 aaa 20S ST", "C28 aaa 20R ST"), "C28aaaS/S+R"),
#C28abbS/S+R
ratio_peaks(., "C28 aBB 20S ST", c("C28 aBB 20S ST", "C28 aBB 20R ST"), "C28abbS/S+R"),
#C29Dia/all
ratio_peaks(., c("C29 Ba 20S ST", "C29 Ba 20R ST"), c("C29 Ba 20S ST", "C29 Ba 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST", "C29 aaa 20S ST", "C29 aaa 20R ST"), "C29Dia/all"),
#C29DiaS/S+R
ratio_peaks(., "C29 Ba 20S ST", c("C29 Ba 20S ST", "C29 Ba 20R ST"), "C29DiaS/S+R"),
#C29abb/all
ratio_peaks(., c("C29 aBB 20S ST", "C29 aBB 20R ST"), c( "C29 aaa 20S ST", "C29 aaa 20R ST", "C29 aBB 20S ST", "C29 aBB 20R ST" ), "C29abb/all"),
#C29aaaS/S+R
ratio_peaks(., "C29 aaa 20S ST", c("C29 aaa 20S ST", "C29 aaa 20R ST") , "C29aaaS/S+R"),
#C29abbS/S+R
ratio_peaks(., "C29 aBB 20S ST", c("C29 aBB 20S ST", "C29 aBB 20R ST"), "C29abbS/S+R"),
#C27Ts/Ts+Tm
ratio_peaks(., "Ts C27 HO", c("Ts C27 HO", "Tm C27 HO"), "C27Ts/Tm"),
#C28BNH29,30/28,30
ratio_peaks(., "29, 30 C28 bisnor HO", c("29, 30 C28 bisnor HO", "28, 30 C28 bisnor HO"), "C28BNH29,30/28,30"),
#C29Ts/Ts+ab
ratio_peaks(., "C29 Ts HO", c( "C29 aB HO", "C29 Ts HO"), "C29Ts/ab"),
#C29ba/ba+ab
ratio_peaks(.,"C29 Ba HO", c("C29 aB HO", "C29 Ba HO"), "C29ba/ab"),
#C29bb/bb+ab
ratio_peaks(., "C29 BB Ho", c("C29 BB Ho", "C29 aB HO"), "C29bb/ab"),
#C30_30nor/30nor+ab
ratio_peaks(., "30-nor C30H HO", c("C30 aB HO", "30-nor C30H HO"), "C30_30nor/ab"),
#C30ba/ba+ab
ratio_peaks(., "C30H Ba HO", c("C30 aB HO", "C30H Ba HO"), "C30ba/ab"),
#C30bb/bb+ab
ratio_peaks(., "C30 BB HO", c("C30 aB HO", "C30 BB HO"), "C30bb/ab"),
#C31S/S+R
ratio_peaks(., "C31 aB HS HO", c("C31 aB HR HO", "C31 aB HS HO"), "C31S/S+R"),
#C32S/S+R
ratio_peaks(., "C32 aB HS HO", c("C32 aB HS HO", "C32 aB HR HO"), "C32S/S+R"),
#C33S/S+R
ratio_peaks(., "C33 aB HS HO", c("C33 aB HS HO", "C33 aB HR HO"), "C33S/S+R"),
#C34S/S+R
ratio_peaks(., "C34 aB HS HO", c("C34 aB HS HO", "C34 aB HR HO") , "C34S/S+R"),
#C35S/S+R
ratio_peaks(., "C35 aB HS HO", c("C35 aB HS HO", "C35 aB HR HO") , "C35S/S+R")
) }) %>% ungroup()
final_data## # A tibble: 19,947 x 35
## file_id peak_name RT.min area.cpm height.cts OG depth rock.g tle
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TSQ3466… 20R 4a,24… 34.7 42909 396389 22.0 102 11.0 4.50
## 2 TSQ3466… 20R, 4a M… 33.4 33439 425331 22.0 102 11.0 4.50
## 3 TSQ3466… 20R, 4a M… 32.8 49529 763046 22.0 102 11.0 4.50
## 4 TSQ3466… 20R, 4a,2… 35.3 26212 404760 22.0 102 11.0 4.50
## 5 TSQ3466… 20S, 4a M… 32.1 49207 882869 22.0 102 11.0 4.50
## 6 TSQ3466… 20S, 4a,2… 35.8 31831 268610 22.0 102 11.0 4.50
## 7 TSQ3466… 20S, 4a,2… 34.0 51613 456842 22.0 102 11.0 4.50
## 8 TSQ3466… 25-nor C2… 37.6 11915 155542 22.0 102 11.0 4.50
## 9 TSQ3466… 28, 30 C2… 37.0 27403 343070 22.0 102 11.0 4.50
## 10 TSQ3466… 29, 30 C2… 35.8 5780 63220 22.0 102 11.0 4.50
## # ... with 19,937 more rows, and 26 more variables: maltene <dbl>,
## # ref_amount_added.ug <dbl>, process <chr>, n_peaks <int>,
## # n_standards <int>, ref_area.cpm <dbl>, amount.ug <dbl>,
## # conc_rock.ug_g <dbl>, conc_tle.ug.g <dbl>, conc_maltene.ug.g <dbl>,
## # calibration <chr>, data <list>, fit <list>, coefficients <list>,
## # intercept <dbl>, intercept_se <dbl>, slope <dbl>, slope_se <dbl>,
## # r2 <dbl>, total_volume.uL <dbl>, total_inject.uL <dbl>,
## # ref_amount_inject_expected.ng <dbl>,
## # ref_amount_inject_measured.ng <dbl>, ref_amount_measured.ug <dbl>,
## # yield <dbl>, ratio <dbl>Bring in other data for comparison (data from Jones et al., (2018))
osisotope <- read_excel(file.path("metadata", "SH1_Osi_forGarrett.xlsx")) %>%
rename(depth = `Depth (m)`) cisotope <- read_excel(file.path("metadata", "Appendix_Table1_geochemistry.xlsx")) %>%
#rename columns
rename(depth = `Abs. depth (m)` , d13c_org = `Average δ13Corg (‰ VPDB)` , carb = `%Carbonate`, TOC = `%TOC`, d13c_carb = `Average δ13Ccarb (‰ VPDB)`) %>%
#remove columns not of interest
select(-`stdev δ13Corg`, -`δ13Ccarb stdev`, -`d18O-avg`, -`d18O stdev`, -`∆13C`, -`d13c_carb`)
cisotope## # A tibble: 146 x 4
## depth d13c_org carb TOC
## <dbl> <dbl> <dbl> <dbl>
## 1 125 -25.6 7.80 1.04
## 2 125 -26.0 13.7 0.835
## 3 125 -25.3 16.1 0.874
## 4 124 -25.5 17.2 1.02
## 5 124 -25.4 10.1 1.05
## 6 124 -25.2 11.4 1.13
## 7 124 -25.2 13.9 1.27
## 8 124 -25.1 16.5 1.58
## 9 123 -25.2 15.6 1.52
## 10 123 -25.3 23.0 0.502
## # ... with 136 more rowshorizontal_lines <-
data_frame(
depth = c(123, 120, 117)
)
carb <- cisotope %>%
ggplot() +
aes(depth, carb) +
geom_point() +
geom_line() +
scale_x_reverse() +
coord_flip() +
ggtitle("carbonate%") +
geom_vline(horizontal_lines,
mapping = aes(xintercept = depth))
TOC <- cisotope %>%
ggplot() +
aes(depth, TOC) +
geom_point() +
geom_line() +
scale_x_reverse() +
coord_flip() +
ggtitle("TOC%") +
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank()) +
geom_vline(horizontal_lines,
mapping = aes(xintercept = depth))
d13c <- cisotope %>%
ggplot() +
aes(depth, d13c_org) +
geom_point() +
geom_line() +
scale_x_reverse() +
coord_flip() +
ggtitle("d13C_org") +
theme(axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank()) +
geom_vline(horizontal_lines,
mapping = aes(xintercept = depth))
os <- osisotope %>%
ggplot() +
aes(x = depth, y = Osi) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip() +
ggtitle("os") +
#theme(axis.text.y = element_blank(),
#axis.ticks.y = element_blank(),
#axis.title.y = element_blank()) +
geom_vline(horizontal_lines,
mapping = aes(xintercept = depth))
#ggplotly(carb)
#ggplotly(TOC)
#ggplotly(d13c)
library(gridExtra)##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
##
## combinegrid.arrange(carb, TOC, d13c, os, ncol=4)## Warning: Removed 3 rows containing missing values (geom_point).
Plot against depth
Sterane - Source
Regular steranes over all steranes
sterane_area <- subset(final_data, peak_name %in% c("C26St/allSt", "C27St/allSt", "C28St/allSt", "C29St/allSt", "C30St/allSt", "C30Me/allSt", "DinoSt/allSt")) %>%
ggplot() +
geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
#facet_grid(~peak_name, scales = "free") +
coord_flip() +
scale_x_reverse() +
scale_y_continuous()
ggplotly(sterane_area)## Warning: Removed 112 rows containing missing values (position_stack).#sterane_area_all <- grid.arrange(carb, TOC, d13c, os, sterane_area, ncol=5) Regular aaa steranes / all regular aaa steranes
regaaa <- subset(final_data, peak_name %in% c("C26/(C26-30)aaaSR","C27/(C26-30)aaaSR", "C28/(C26-30)aaaSR", "C29/(C26-30)aaaSR", "C30/(C26-30)aaaSR")) %>%
ggplot() +
geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
#facet_wrap(~peak_name, scales = "free") +
coord_flip() +
scale_x_reverse() +
scale_y_continuous()
#theme(axis.text.y = element_blank(),
# axis.ticks.y = element_blank(),
# axis.title.y = element_blank())
ggplotly(regaaa)## Warning: Removed 80 rows containing missing values (position_stack).#reaaa_all <- grid.arrange(d13c, regaaa, ncol=2)aaa&abb
aaa <- subset(final_data, peak_name %in% c("C27/C27+C28aaa&abb", "C27/C27+C29aaa&abb", "C28/C28+C27aaa&abb", "C28/C28+C29aaa&abb", "C29/C29+C27aaa&abb", "C29/C29+C28aaa&abb")) %>%
ggplot() +
geom_point() +
geom_line() +
#geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
facet_grid(~peak_name) +
coord_flip() +
scale_x_reverse() +
scale_y_continuous()
ggplotly(aaa)#reaaa_all <- grid.arrange( d13c, aaa, ncol=7)4Me_TriMes
TriMe <- subset(final_data, peak_name %in% c("4Me_TriMe/Me_C26St", "4Me_TriMe/Me_C27St", "4Me_TriMe/Me_C28St", "4Me_TriMe/Me_C29St", "4Me_TriMe/Me_C30St", "4Me_TriMe/Me_allSt")) %>%
ggplot() +
geom_point() +
geom_line() +
#geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
facet_grid(~peak_name) +
coord_flip() +
scale_x_reverse()
ggplotly(TriMe)Sterane over all ratios
yet <- subset(final_data, peak_name %in% c("C26-30St/C26-C30St_regHo", "C27-C30aaaSt/C27-C30aaaSt+regHo")) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(yet)Hopanes - Source
Tricyclics
tri <- subset(final_data, peak_name %in% c("C19/tricyclics" , "C20/tricyclics" , "C21/tricyclics" , "C22/tricyclics" , "C23/tricyclics" , "C24/tricyclics" , "C25/tricyclics" , "C26/tricyclics")) %>%
ggplot() +
geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(tri)## Warning: Removed 128 rows containing missing values (position_stack).tri_all <- subset(final_data, peak_name %in% c("C19/C19+23", "C20/C20+23", "tricyclics/all")) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(tri_all)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning: Removed 48 rows containing non-finite values (stat_smooth).Hopanes over steranes
vertical_lines <- data_frame(
one = 1
)
host <- subset(final_data, peak_name == "Ho/St") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
geom_hline(vertical_lines,
mapping = aes(yintercept = one)) +
scale_x_reverse() +
coord_flip()
ggplotly(host)2Me Hopanes
mehi <- subset(final_data, peak_name %in% c("C31_2MHI", "C31_35_2MHI", "C31_2-MHI/C27-C30Steranes"))%>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(mehi)3Me Hopanes
threemehi <- subset(final_data, peak_name %in% c( "C31_35_3MHI(%)", "C31 3-MHI")) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(threemehi)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning: Removed 32 rows containing non-finite values (stat_smooth).C29 aB Hopane
abs <- subset(final_data, peak_name%in% c("C29ab/allHoab", "C29ab/C29ab+C30ab")) %>%
filter(ratio > 0.1) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(abs)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'ab/all ho
ho <- subset(final_data, peak_name %in% c("C29ab/allHoab","C30ab/allHoab", "C31ab/allHoab", "C32ab/allHoab", "C33ab/allHoab", "C34ab/allHoab", "C35ab/allHoab")) %>%
ggplot() +
geom_area(mapping = aes(fill = peak_name)) +
aes(x = depth, y = ratio, color = peak_name) +
#facet_wrap(~peak_name, scales = "free") +
coord_flip() +
scale_x_reverse() +
scale_y_continuous()
ggplotly(ho)## Warning: Removed 112 rows containing missing values (position_stack).Stratification
HHIGI <- subset(final_data, peak_name %in% c( "GI", "HHI")) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(HHIGI)Miscelaneous Hopane ratios
subset(final_data, peak_name== "OleananeIndex") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
# facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()## Warning: Removed 16 rows containing missing values (geom_point).## Warning: Removed 16 rows containing missing values (geom_path).
subset(final_data, peak_name== "C35/C35+C34") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()## Warning: Removed 16 rows containing missing values (geom_point).## Warning: Removed 16 rows containing missing values (geom_path).
subset(final_data, peak_name== "28,30BNH/28,30BNH+C30") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line()+
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()## Warning: Removed 16 rows containing missing values (geom_point).## Warning: Removed 16 rows containing missing values (geom_path).
Thermal Maturity
C27Dia/Reg
dia <- subset(final_data, peak_name == "C27Dia/Reg") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(dia)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning: Removed 16 rows containing non-finite values (stat_smooth).DiaS/S+R
diasr <- subset(final_data, peak_name%in% c("C28DiaS/S+R" , "C29DiaS/S+R")) %>%
filter(depth != 116.490) %>% filter(depth != 116.900) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(diasr)C27Regabb/aaa
twentyseven<- subset(final_data, peak_name== "C27Reg_abb/aaa") %>%
filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_line() +
geom_point() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(twentyseven)aaa_S/S+R
aaa<- final_data %>%
filter(peak_name %in% c("C27Regaaa_S/S+R", "C28aaaS/S+R", "C29aaaS/S+R")) %>%
filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_line() +
geom_point() +
facet_grid(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(aaa)abb_s/s+r
abb <- subset(final_data, peak_name %in% c("C27Regabb_S/S+R", "C28abbS/S+R", "C29abbS/S+R")) %>%
filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(abb)C28/9Dia/all
Dia <- subset(final_data, peak_name %in% c("C28Dia/all", "C29Dia/all")) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(Dia)C28/9abb/all
eightnine <- subset(final_data, peak_name %in% c("C28abb/all", "C29abb/all")) %>%
filter(depth != 115.885) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(eightnine)C27Ts/Tm
tstm <- subset(final_data, peak_name== "C27Ts/Tm") %>%
filter(depth != 115.885) %>% filter(depth != 120.405) %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(tstm)C28BNH29,30/28,30
bnh <- subset(final_data, peak_name== "C28BNH29,30/28,30") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(bnh)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning: Removed 17 rows containing non-finite values (stat_smooth).C29Ts/ab
tsab<- subset(final_data, peak_name== "C29Ts/ab") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_line() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(tsab)C29,30ba/ab
baab <- subset(final_data, peak_name %in% c("C29ba/ab", "C30ba/ab")) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(baab)C29bb/ab
bbab <- subset(final_data, peak_name %in% c("C29bb/ab", "C30bb/ab")) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(bbab)C30_30nor/ab
thirtynor <- subset(final_data, peak_name== "C30_30nor/ab") %>%
ggplot() +
aes(x = depth, y = ratio) +
geom_point() +
geom_smooth() +
facet_wrap(~peak_name, scales = "free") +
scale_x_reverse() +
coord_flip()
ggplotly(thirtynor)## `geom_smooth()` using method = 'loess' and formula 'y ~ x'## Warning: Removed 16 rows containing non-finite values (stat_smooth).C30 ab/ba
thabba <- subset(final_data, peak_name %in% c("C30 aB HO", "C30H Ba HO")) %>%
ggplot() +
aes(x = depth, y = conc_rock.ug_g, color = peak_name) +
geom_point() +
geom_line() +
#facet_wrap(~peak_name) +
scale_x_reverse() +
coord_flip()
ggplotly(thabba)All Ho S/R
srho <- final_data %>%
filter(peak_name %in% c("C31S/S+R", "C32S/S+R", "C33S/S+R", "C34S/S+R", "C35S/S+R")) %>%
filter(ratio > 0.1) %>%
ggplot() +
aes(x = depth, y = ratio, color = peak_name) +
geom_point() +
geom_line() +
#facet_grid(~peak_name) +
scale_x_reverse() +
coord_flip()
ggplotly(srho)Everything
erry <- final_data %>%
filter(peak_name == "everything") %>%
ggplot() +
aes(x = depth, y = conc_rock.ug_g) +
geom_point() +
geom_line() +
#facet_grid(~peak_name) +
scale_x_reverse() +
coord_flip()
ggplotly(erry)Chunk to check plots
outcome <- calib_data %>%
group_by(file_id) %>%
select(file_id, peak_name, depth, area.cpm, conc_rock.ug_g) %>%
do({
bind_rows(.,
ratio_peaks(., "C27 aB 20S ST", "C27 aB 20R ST", "C27Dia_S/R")
)
}) %>%
filter(#!str_detect(file_id, "TSQ3779"),
str_detect(peak_name, "C27 aB 20R ST"))
#str_detect(peak_name, "aB"))
outcome## # A tibble: 82 x 6
## # Groups: file_id [82]
## file_id peak_name depth area.cpm conc_rock.ug_g ratio
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 TSQ3466_GB_OG022 C27 aB 20R ST 102 24465 9.08 NA
## 2 TSQ3467_GB_OG023 C27 aB 20R ST 101 30269 11.6 NA
## 3 TSQ3468_GB_OG025 C27 aB 20R ST 98.9 38685 15.1 NA
## 4 TSQ3469_GB_OG026 C27 aB 20R ST 98.1 2625 1.89 NA
## 5 TSQ3472_GB_OG027 C27 aB 20R ST 96.9 4195 1.62 NA
## 6 TSQ3473_GB_OG019 C27 aB 20R ST 105 651 0.416 NA
## 7 TSQ3474_GB_OG020 C27 aB 20R ST 104 1537 0.852 NA
## 8 TSQ3475_GB_OG021 C27 aB 20R ST 103 7266 3.40 NA
## 9 TSQ3476_GB_OG018 C27 aB 20R ST 106 3130 1.06 NA
## 10 TSQ3481_GB_OG002 C27 aB 20R ST 125 1423 0.494 NA
## # ... with 72 more rows